P1401: UNBIASED, LONGITUDINAL ANALYSIS OF THE INFLAMMATORY RESPONSE OF HSPCS AT THE SINGLE CELL LEVEL RESOLVES CONTROVERSIES REGARDING THE HSPCS STRESS RESPONSE
Authors: Y. Demerdash, B. J. Bouman, L. Haghverdi, M. Essers
Journal: HemaSphere (2022)

Background: Research investigating inflammatory stress responses in the hematopoietic system have mainly focused on one time-point and one defined cell population. Surface markers typically used to isolate hematopoietic stem and progenitor cells (HSPCs) massively change upon inflammation, which questions the reliability of using flow cytometry to study the system upon inflammation. Aims: Here we will investigate the dynamics of stress responses in the hematopoietic stem and progenitor compartment at the single-cell level, independent of the use of defined surface markers. Methods: Hence, we performed a time series single-cell sequencing experiment on sorted HSPCs (Linneg cKit+), 3, 24 and 72 hours after injection of mice with the pro-inflammatory cytokine IFNa to investigate the acute inflammation response of bone marrow hematopoietic stem and progenitor cells (HSPCs) in time. Results: Marker independent abundance analysis in our dataset based on the transcriptional profile of the cell clusters highlight both an HSC enrichment as well as a myeloid depletion over time. The dramatic depletion of myeloid progenitors was not restored within 72h post treatment and is possibly linked to impaired myeloid differentiation programs in the HSCs, suggested by decreased expression of myeloid differentiation factors (ex. MPO, Elane and Ctsg). A longitudinal single-cell dataset covering multiple timepoints after treatment poses new challenges for the computational analyses. Current single-cell algorithms studying the progression of cells in time rely on the assumption that proximity of two cell states is a measure for the typical transition time between them. However, in a time series which covers both response and recovery this assumption is violated. Therefore, we introduce a new approach for the identification of pseudotime. Our method allows us to explore the expression of genes in continuous time, rather than looking at the four experimental timepoints only. Using our pseudotime approach, we discover a variety of different gene responses of the HSPCs to the treatment. Additionally, we found that most differentially expressed genes show the most extreme response in the HSCs. Thus, even though the whole system is sensing the treatment, the underneath response is very heterogeneous, with the earliest, strongest response in the HSC clusters themselves. Summary/Conclusion: In conclusion, using single cell sequencing analysis over time, for the first time we have been able to study the impact effect of IFNa treatment on the whole HSPCs compartment at the single cell level in an unbiased manner. Moreover, adding the dimension of time helped us infer the dynamics of the inflammatory process in the HSPCs compartment. Our study not only provides new insights into the impact of inflammatory stress on the HSPC compartment but also serves as a guideline for the analysis of longitudinal response datasets in the hematopoietic system.